Evaluation on China's forestry resources efficiency based on big data

Journal of Cleaner Production

Volumn 142, Issue , 2017, Pages 513-523

  Li, Lei ^a   Hao, Tongtong ^a   Chi, Ting ^a  

^a TIANJIN UNIVERSITY   (China)

Author keywords

Big data; China's forestry resources; DEA; Malmquist total factor productivity index

Indexed keywords

DATA ENVELOPMENT ANALYSIS; EFFICIENCY; FORESTRY; NATURAL RESOURCES; POPULATION STATISTICS; PRODUCTIVITY; TIMBER;

ECOLOGICAL FACTORS; FORESTRY RESOURCES; OPERATION AND MANAGEMENT; OVERALL EFFICIENCY; RESEARCH AND EVALUATION; SCIENCE AND TECHNOLOGY; TECHNOLOGY UTILIZATION; TOTAL FACTOR PRODUCTIVITY;

BIG DATA;

EID: 84959457308     PISSN: 09596526     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jclepro.2016.02.078     Document Type: Article

References (41)

1. Adhikari, Bhim, Property rights and natural resources: impact of common property institutions on community-based resource management. Rio de Janeiro: Third Annual Global Development Network Conference, 2001.
2. Alexander, S.A., Palmer, C.J., Forest health monitoring in the United States: first four years. Environ. Monitor. Assess. 55 (1999), 267–277.
3. Banker, R.D., et al. Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manag. Sci. 30 (1984), 1078–1092.
4. Baru, C., et al. Benchmarking big data systems and the big data top 100 list. Big Data 1:1 (2013), 60–64.
5. Camargo-Vega, et al. Conociendo big data. Universidad Pedagógica y Tecnológica de Colombia. Tunja 24:38 (2015), 63–77.
6. Caves, D.W., et al. The economic theory of index numbers and measurement of input, output, and productivity. Econometrica 50 (1982), 1393–1414.
7. Charnes, A., et al. Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2 (1978), 429–444.
8. Chen, Wenhui, et al. The forest resources input–output model: an application in China. Ecol. Indic. 51 (2015), 87–97.
9. Cherniwchan, J., Economic growth, industrialization, and the environment. Resour. Energy Econ. 34 (2012), 442–467.
10. China Forestry Statistical Yearbook, China Forestry. 2005–2013, Publishing House, Beijing, China (in Chinese).
11. Cooper, W.W., et al. Handbook on Data Envelopment Analysis. 2004, Kluwer Academic Publishers, Boston.
12. Emi, U., et al. Grain for green: cost-effectiveness and sustainability of China's conservation set-aside program. Land Econ. 2 (2005), 247–264.
13. Fare, R., et al. Production Frontiers. 1994, Cambridge Press, New York.
14. Fried, et al. Accounting for environmental effects and statistical noise in data envelopment analysis. J. Prod. Anal. 17:1 (2002), 157–174.
15. Gandomi, Amir, Haider, Murtaza, Beyond the hype: big data concepts, methods, and analytics. Int. J. Inform. Manag. 35 (2015), 137–144.
16. Garlasu, Dan, A big data implementation based on grid computing. 11th RoEduNet International Conference – Networking in Education and Research, Sinaia, Romania, Jan 17–19, 2013.
17. Giuntoli, J., et al. Domestic heating from forest logging residues: environmental risks and benefits. J. Clean. Prod. 99 (2015), 206–216.
18. Gonzalez, S., et al. Comparing environmental impacts of different forest management scenarios for maritime pine biomass production in France. J. Clean. Prod. 64 (2014), 356–367.
19. Hacer, O., Yasar, A., A national study of efficiency for dialysis centers: an examination of market competition and facility characteristics for production of multiple dialysis outputs. Health Serv. Res. 37:3 (2002), 711–732.
20. Hyde, W.D., et al. Forest economics and Policy Analysis: an Overview. (World Bank Discussion Paper, No. 134), 1991, The World Bank, Washington D.C.
21. Juan, et al. Data envelopment analysis (DEA) index to measure the accessibility impacts of new infrastructure investments: the case of the high- speed train corridor Madrid-Barcelona-French border. Reg. Stud. 38:6 (2004), 697–712.
22. Kim, Sung-Hwan, et al. Attribute relationship evaluation methodology for big data security. 3rd International Conference on IT Convergence and Security, 2013, ICITCS, Macau.
23. Lee, J.Y., Using DEA to measure efficiency in forest and paper companies. For. Prod. J. 55 (2005), 58–66.
24. Li, L., et al. Production efficiency evaluation of energy companies based on the improved super-efficiency data envelopment analysis (DEA) considering undesirable outputs. Math. Comput. Model. 58:5–6 (2013), 1057–1067.
25. Li, S.L., et al. A super-efficiency model for ranking efficient units in data envelopment analysis. Appl. Math. Comput. 84:2 (2007), 638–648.
26. Lu, Tianbo, et al. Next big thing in big data: the security of the ICT supply chain. ASE/IEEE International Conference on Social Computing (SocialCom), Washington, DC, 2013.
27. Ma, S., et al. A case study of phosphorus chemical firm's application of resource efficiency and eco-efficiency in industrial metabolism under circular economy. J. Clean. Prod. 87 (2015), 839–849.
28. Malmquist, S., Index numbers and indifference surfaces. Trabajos Estadistica 4 (1953), 209–242.
29. Manyika, James, et al. Big Data: the Neat Frontier for Innovation, Competition, and Productivity. 2011, McKinsey Global Institute.
30. Mattila, T., et al. An environmentally extended input–output analysis to support sustainable use of forestry resources. Open For. Sci. 4 (2011), 15–23.
31. Napoles-Rivers, Fabricio, et al. Sustainable water management for macroscopic systems. J. Clean. Prod. 47 (2013), 102–117.
32. Schulze, E.D., Schulze, I., Sustainable foresting: easier said than done. Science, 327(5968), 2010, 957.
33. Sinuany-Stern, Z., et al. Academic departments efficiency in DEA. Comput. Oper. Res. 21:5 (1994), 543–556.
34. Song, M., Analysis of the operating efficiency of online game industry in China actualized by DEA. J. Softw. 5:11 (2010), 1216–1223.
35. Song, M., et al. Statistical analysis and combination forecasting of environmental efficiency and its influential factors since China entered the WTO: 2002–2010–2012. J. Clean. Prod. 42 (2013), 42–51.
36. Viitala, E.J., Hanninen, H., Measuring the efficiency of public forestry organizations. For. Sci. 44 (1998), 298–307.
37. Weiss, R., Zgorski, L., Obama Administration Unveils ‘Big Data’ Initiative: Announces $200 Million in New R&D Investment. 2012, Office of Science and Technology Policy, Executive Office of the President, White House, Washington.
38. Yasar, A., et al. Efficiency evaluation of skilled nursing facilities. J. Med. Syst. 22:4 (1998), 211–224.
39. Yunosa, J.M., Hawdon, D., The efficiency of the National Electricity Board in Malaysia: an intercountry comparison using DEA. Energy Econ. 19 (1997), 255–269.
40. Zhelev, T.K., On the integrated management of industrial resources incorporating finances. J. Clean. Prod. 13 (2005), 469–474.
41. Zhou, P., et al. Measuring environmental performance under different environmental DEA technologies. Energy Econ. 30 (2008), 1–14.